Triple
T27882770
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MMSM |
E705137
|
entity |
| Predicate | associatedAirportLocatedIn |
P2903
|
FINISHED |
| Object | Zumpango, State of Mexico |
—
|
NE NERFINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Zumpango, State of Mexico | Statement: [MMSM, associatedAirportLocatedIn, Zumpango, State of Mexico]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedAirportLocatedIn Context triple: [MMSM, associatedAirportLocatedIn, Zumpango, State of Mexico]
-
A.
associatedAirport
Indicates a relationship where an entity is linked or connected to a specific airport, typically as its relevant or corresponding airport.
-
B.
associatedAirportFocusCityFor
Indicates that an airport serves as a designated focus city for a particular airline or carrier.
-
C.
airportLocatedIn
chosen
Indicates that an airport is geographically situated within a specific administrative or territorial area.
-
D.
associatedAirportServes
Indicates that a given airport provides service to, or is used by, the associated entity (such as a city, region, or facility).
-
E.
associatedHubAirport
Indicates that one entity serves as a primary or hub airport functionally linked to the other entity.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ef96b39c448190a9b3aa6672a5168f |
completed | April 27, 2026, 5:02 p.m. |
| NER | Named-entity recognition | batch_6a007dd341108190a1d03eab46041694 |
completed | May 10, 2026, 12:45 p.m. |
| PD | Predicate disambiguation | batch_6a007b1fe2a881909ec50a1e65e4651b |
completed | May 10, 2026, 12:33 p.m. |
Created at: April 27, 2026, 6:31 p.m.